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Artículo
Liquid State Machine on SpiNNaker for Spatio-Temporal Classification Tasks
(Frontiers Media S.A., 2022-03-14)
Liquid State Machines (LSMs) are computing reservoirs composed of recurrently connected Spiking Neural Networks which have attracted research interest for their modeling capacity of biological structures and as promising ...
Ponencia
Fast Pipeline 128x128 Pixel Spiking Convolution Core for Event-Driven Vision Processing in FPGAs
(IEEE. Institute of Electrical and Electronics Engineers, 2015)
This paper describes a digital implementation of a parallel and pipelined spiking convolutional neural network (SConvNet) core for processing spikes in an event-driven system. Event-driven vision systems use typically ...
Ponencia
An AER handshake-less modular infrastructure PCB with x8 2.5Gbps LVDS serial links
(IEEE Computer Society, 2014)
Nowadays spike-based brain processing emulation is taking off. Several EU and others worldwide projects are demonstrating this, like SpiNNaker, BrainScaleS, FACETS, or NeuroGrid. The larger the brain process emulation ...
Artículo
A Configurable Event-Driven Convolutional Node with Rate Saturation Mechanism for Modular ConvNet Systems Implementation
(Frontiers Media, 2018)
Convolutional Neural Networks (ConvNets) are a particular type of neural network often used for many applications like image recognition, video analysis or natural language processing. They are inspired by the human brain, ...
Ponencia
Sensor de humedad del suelo de bajo coste para control de regadíos
(2001)
This paper presents a low-cost system to measure soil humidity for application in irrigation control. It is based in the simultaneous measurement of the real and imaginary parts of the impedance of a volume of soil ...
Ponencia
On scalable spiking convnet hardware for cortex-like visual sensory processing systems
(IEEE Computer Society, 2010)
This paper summarizes how Convolutional Neural Networks (ConvNets) can be implemented in hardware using Spiking neural network Address-Event-Representation (AER) technology, for sophisticated pattern and object recognition ...
Artículo
Plasticity in memristive devices for spiking neural networks
(Frontiers Media, 2015)
Memristive devices present a new device technology allowing for the realization of compact non-volatile memories. Some of them are already in the process of industrialization. Additionally, they exhibit complex multilevel ...
Artículo
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity
(IEEE Computer Society, 2019)
Inference of Deep Neural Networks for stream signal (Video/Audio) processing in edge devices is still challenging. Unlike the most state of the art inference engines which are efficient for static signals, our brain is ...
Ponencia
Experimental Body-input Three-stage DC offset Calibration Scheme for Memristive Crossbar
(IEEE, 2020)
Reading several ReRAMs simultaneously in a neuromorphic circuit increases power consumption and limits scalability. Applying small inference read pulses is a vain attempt when offset voltages of the read-out circuit are ...
Ponencia
Live Demonstration: Multiplexing AER Asynchronous Channels over LVDS Links with Flow-Control and Clock- Correction for Scalable Neuromorphic Systems
(IEEE Computer Society, 2017)
In this live demonstration we exploit the use of a serial link for fast asynchronous communication in massively parallel processing platforms connected to a DVS for realtime implementation of bio-inspired vision processing ...